Financial Performance Analysis Using the Merec-Based Cobra Method: An Application to Traditional and Low-Cost Airlines
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School of Civil Aviation, Dicle University, Diyarbakır, Turkey
Submission date: 2023-06-13
Final revision date: 2023-12-16
Acceptance date: 2024-02-19
Publication date: 2024-06-28
Corresponding author
Veysi Asker   

School of Civil Aviation, Dicle University, Diyarbakır, Turkey
GNPJE 2024;318(2):35-52
The aim of this study is to examine the impact of the COVID-19 pandemic on the financial performance of traditional and low-cost airlines. In this context, the financial performance of 32 traditional and 14 low-cost airlines operating in different regions of the world was analysed using the Merec-based Cobra method for the before and during COVID-19 pandemic period (2018–2021). First, the financial ratios of the airlines were weighted using the Merec method, then the financial performance ranking of the airlines was conducted using the Cobra method. According to the results of the Cobra method, Ryanair (FR) was found to have the best financial performance in 2018 and 2020. Meanwhile, Allegiant Travel (G4) led the way in 2019, and Thai Airways (TG) came out on top in 2021. According to the analysis results, low-cost airlines such as Southwest Airlines (WN), Wizz Air (W6), Allegiant Air Travel (G4), and Ryanair (FR) showed better performance than a significant portion of traditional airlines in the period before the COVID- 19 pandemic. In contrast, during the COVID-19 pandemic, low-cost airlines such as Spring Airlines (9C), Air Arabia (G9), Cebu Air (5J), Easyjet (U2), and Jetblue Airways (B6) demonstrated worse performance than a significant portion of traditional airlines.
Abate M., Christidis P., Purwanto A. J. [2020], Government support to airlines in the aftermath of the COVID-19 pandemic, Journal of Air Transport Management, 89 (101931): 1–15.
Aigner D., Lovell C. K., Schmidt P. [1977], Formulation and estimation of stochastic frontier production function models, Journal of Econometrics, 6 (1): 21–37.
Albers S., Rundshagen V. [2020], European airlines’ strategic responses to the COVID-19 pandemic (January–May 2020), Journal of Air Transport Management, 101863: 1–7.
Ali N. Y., See K. F. [2023], Revisiting an environmental efficiency analysis of global airlines: A parametric enhanced hyperbolic distance function, Journal of Cleaner Production, 394: 1–12.
Asker V. [2021a], Measurement of efficiency with two-stage data envelopment analysis in airline companies, MANAS Journal of Social Studies, 10 (4): 2373–2385.
Asker V. [2021b], Operational and financial performance analysis with malmquist total factor productivity index: an application in selected airlines, Erciyes University Journal of Economics and Administrative Sciences, 59: 435–460.
Asker V. [2022], Investigation of financial performance in traditional and lowcost airlines by Malmquist total factor productivity index, Dicle University Social Sciences Institute Journal, 2022 (29): 435–452.
Asker V., Aydın N. [2021], Financial Efficiency Measurement in Airlines and Determining Factors of Efficiency, Alanya Academic Review Journal, 5 (2): 793–814.
Asker V., Ustaömer T. C. [2022], Financial efficiency analysis the Malmquist TFP method: an application on star alliance member airlines, Bingol University Journal of Economics and Administrative Sciences, 6 (2): 39–57.
Assaf G. A., Tsionas M. G., Gillen D. [2020], Measuring firm performance: Differentiating between uncontrollable and controllable bad outputs, Tourism Management, 80: 1–18.
Atay M., Eroğlu Y., Seçkiner Ulusam S. [2022], Does fleet standardization matter on profitability and financial policy response of airlines during COVID-19 pandemics in the US?, EURO Journal on Transportation and Logistics, 11 (3): 2–15.
Atems B., Yimga J. [2021], Quantifying the impact of the COVID-19 pandemic on US airline stock prices, Journal of Air Transport Management, 97: 1–18.
Bakır M., Akan Ş., Kiracı K., Karabasevic K., Stanujkıc D., Popovic G. [2020], Multıple-Crıteria Approach of the Operational Perfomance Evaluation in the Airline Industry Evidence from Emerging Market, Romanian Journal of Economic Forecasting, 2 (2): 149–172.
Barros C. P., Wanke P. [2015], An analysis of African airlines efficiency with two-stage TOPSIS and neural networks, Journal of Air Transport Management, 44–45 (2): 90–102.
Bombelli A. [2020], Integrators’ global networks: A topology analysis with insights into the effect of the COVID-19 pandemic, Journal of Transport Geography, 102815: 1–24.
Budd L., Ison S., Adrienne N. [2020], European airline response to the COVID-19 pandemic – Contraction, consolidation and future considerations for airline business and management, Research in Transportation Business & Management, 37 (5): 1–7.
Cao Q., Lv J., Zhang J. [2015], Productivity efficiency analysis of the airlines in China after deregulation, Journal of Air Transport Management, 42 (1): 135–140.
Caves D., Christensen L. R., Diewert W. E. [1982], Multilateral comparisons of output, input, and productivity using superlative index numbers, The Economic Journal, 92 (365): 78–86.
Charnes A., Cooper W. W., Rhodes E. [1978], Measuring the efficiency of decision making units, European Journal of Operational Research, 2 (6): 429–444.
Cui Q., Li Y. [2017], Airline efficiency measures using a dynamic epsilon-based measure model, Transportation Research Part A, 100: 121–134.
Czerny A. İ., Fu X., Lei Z., Oum T. H. [2021], Post pandemic aviation market recovery: Experience and lessons from China, Journal of Air Transport Management, 90: 1–10.
Gigoviç L., Pamucar D., Bajiçüc Z., Milicevic M. [2016], The combination of expert judgment and GIS-MAIRCA analysis for the selection of sites for ammunition depots, Sustainability, 8 (372): 1–30.
Gramani M. [2012], Efficiency decomposition approach: A cross-country airline analysis, Expert Systems with Applications, 39 (5): 5815–5819.
Haq R., Saeed M., Mateen N., Siddiqui F., Naqvi M., Yi J. B., Ahmed S. [2022], Sustainable material selection with crisp and ambiguous data using single-valued neutrosophic-MEREC–MARCOS framework, Applied Soft Computing, 128: 1–21.
Heydari C., Omrani H., Taghizadeh R. [2020], A fully fuzzy network DEA-range adjusted measure model for evaluating airlines efficiency: A case of Iran, Journal of Air Transport Management, 53 (2): 1–18.
Hong S., Zhang A. [2010], An efficiency study of airlines and air cargo/passenger divisions: a DEA approach, World Review of Intermodal Transportation Research, 3 (1/2): 137–149.
Hsu C.‑C., Liou J. J. [2013], An outsourcing provider decision model for the airline industry, Journal of Air Transport Management, 28: 40–46.
Hwang C.‑L., Yoon K. [1981], Multiple attribute decision making: methods and applications, Springer-Verlag, New York.
IATA [2018], International Air Transport Association Annual Review 2018, Boston.
ICAO [2022], Economic Impacts of COVID-19 on Civil Aviation,
Jandghi G., Ramshini M. [2014], A performance measurement model for automotive and petrochemical companies using FAHP and CCR Method, European Journal of Academic Essays, 1 (2): 80–92.
Jaroenjitrkam A., Kotcharin S., Maneenop S. [2023], Corporate resilience to the COVID-19 pandemic: Evidence from the airline industry, The Asian Journal of Shipping and Logistics, 39 (2023): 26–36.
Kaya G., Aydın U., Ülengin B., Almula Karadayı M., Ülengin F. [2023], How do airlines survive? An integrated efficiency analysis on the survival of airlines, Journal of Air Transport Management, 107: 1–14.
Keshavarz-Ghorabae M., Amiri M., Zavadskas K., Turskis Z., Antucheviciene J. [2021], Determination of objective weights using a new method based on the removal effects of criteria, Symmetry, 13 (4): 1–20.
Khezrimotlagh D., Kaffash S., Zhu J. [2022], U. S. airline mergers’ performance and productivity change, Journal of Air Transport Management, 102 (2): 1–19.
Kiracı K. [2019a], Does Joining Global Alliances Affect Airlines Financial Perfomance, in: Akar C., Kapucu H. (ed.), Contemporary Challenges in Business and Life Sciences: 39–59, IJOPEC, Baltimore.
Kiracı K. [2019b], The Impact of the Global Financial Crisis on Airlines, in: Yıldız H., Aybar A. S. (ed.), Research in Economics, Econometrics & Finance: 257–284, IJOPEC, London.
Kiracı K., Asker V. [2021], Crisis in the air: A multi-dimensional analysis of the impact of the COVID-19 pandemic on airline performance, Finance-Political & Economic Comments, 657: 33–60.
Kiracı K., Bakır M. [2019], Application of performance measurment in airlines with CRITIC based EDAS method, Pamukkale University Journal of Social Sciences Institute, 13 (35): 157–174.
Kiracı K., Bakır M. [2020], Evaluation of airlines performance using an integrated CRITIC and CODAS methodology: The case of star alliance member airlines, Studies in Business and Economics, 15 (1): 83–99.
Kiracı K., Yaşar M. [2020], The determinants of airline operational performance: an empirical study on major world airlines, Sosyoekonomi, 28 (48): 107–117.
Kottas A., Madas M. A. [2018], Comparative efficiency analysis of major international airlines using data envelopment analysis: Exploring effects of alliance membership and other operational efficiency determinants, Journal of Air Transport Management, 70 (2): 1–17.
Krstic M., Agnusdei G. P., Miglietta P. P., Tadic S., Roso V. [2022], Applicability of industry 4.0 technologies in the reverse logistics: A circular economy approach based on comprehensive distance based ranking (COBRA) method, Sustainability, 14: 1–30.
Lin Y.‑H., Hong C.‑F. [2019], Efficiency and effectiveness of airline companies in Taiwan and mainland China, Asia Pacific Management Review, 24 (3): 1–10.
Lozano S., Gutierrez E. [2014], A slacks-based network DEA efficiency analysis of European airlines, Transportation Planning and Technology, 37 (7): 623–637.
Lu W.‑M., Wang W.‑K., Hung S.‑W., Lu E.‑T. [2012], The effects of corporate governance on airline performance: production and marketing efficiency perspectives, Transportation Research Part E, 48 (2): 529–544.
Mahmoudi R., Emrouznejad A. [2022], A multi-period performance analysis of airlines: A game-SBM-NDEA and Malmquist Index approach, Research in Transportation Business & Management, 42 (1): 1–15.
Meeusen W., Broeck J. v. [1977], Efficiency estimation from Cobb-Douglas production functions with composed error, International Economic Review, 18 (2): 435–444.
Merkert R. [2022], The impact of engine standardization on the cost efficiency of airlines, Research in Transportation Business & Management, 42 (1): 1–11.
Merkert R., Hensher D. A. [2011], The impact of strategic management and fleet planning on airline efficiency – A random effects Tobit model based on DEA efficiency scores, Transportation Research Part A, 45 (7): 686–695.
Merkert R., Williams G. [2013], Determinants of European PSO airline efficiency evidence from a semi-parametric approach, Journal of Air Transport Management, 29 (3): 11–16.
Nguyen M.‑A. T., Yu M.‑M., Lirn T.‑C. [2022], Revenue efficiency across airline business models: A bootstrap non-convex meta-frontier approach, Transport Policy, 117 (1):108–117.
Omrani H., Soltanzadeh E. [2016], Dynamic DEA models with network structure: An application for Iranian airlines, Journal of Air Transport Management, 57 (2): 52–61.
Opricovic S., Tzeng G.‑H. [2004], Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS, European Journal of Operational Research, 156 (2): 445–455.
Pereira D., Mello J. [2021], Efficiency evaluation of Brazilian airlines operations considering the COVID-19 outbreak, Journal of Air Transport Management, 91 (2): 1–6.
Perez P. F., Vazquez X. H., Carou D. [2022], The impact of the COVID-19 crisis on the US airline market: Are current business models equipped for upcoming changes in the air transport sector? Case Studies on Transport Policy, 10: 647–656.
Pineda P. J., Lİou J. J., Hsu C.‑C., Chuang Y.‑C. [2018], An integrated MCDM model for improving airline operational and financial performance, Journal of Air Transport Management, 68 (2): 103–117.
Pires H. M., Fernandes E. [2012], Malmquist financial efficiency analysis for airlines, Transportation Research Part E, 48 (5): 1049–1055.
Popoviç G., Pucar D., Smarandache F. [2022], MEREC–COBRA approach in e-commerce Development Strategy Selection, Journal of Process Management and New Technologies, 10 (3–4): 66–74.
Razaei J. [2015], Best-worst multi-criteria decision-making method, Omega, 53 (2015): 49–57.
Saaty R. W. [1987], The analytic hierarchy process – what it is and how it is used, Mathematical Modelling, 9 (3–5): 161–176.
Saini A., Truong D., Pan J. Y. [2022], Airline efficiency and environmental impacts – Data Envelopment Analysis, International Journal of Transportation Science and Technology, 11 (4): 1–19.
Steviç Z., Pamucar D., Puska A., Cahtterjee P. [2020], Sustainable supplier selection in healthcare industries using a new MCDM method: Measurement of alternatives and ranking according to compromise solution (MARCOS), Computers & Industrial Engineering, 140: 106231.
Tanrıverdi G., Eryaşar M. [2022], Global airline alliances and during the COVID-19 Crisis: Exploring the critical succes factors through CRITIC–CoCoSo methods, Anadolu University Journal of Economics and Administrative Sciences, 23 (4): 177–201.
Turskıs Z., Juodagalviene B. [2016], A novel hybrid multi-criteria decision-making model to assess a stairs shape for dwelling houses, Journal Of Civil Engineering and Management, 22 (8): 1078–1087.
Wang W.‑K., Lin F., Ting I. K., Kweh Q. L., Lu W.‑M., Chiu T.‑Y. [2017], Does asset-light strategy contribute to the dynamic efficiency of global airlines?, Journal of Air Transport Management, 62 (3): 99–108.
Wenzel M., Stanske S., Lieberman M. B. [2023], Strategic responses to crisis, Transportation Research Part A, 170: 1–22.
Yalçin A. S., Kılıç H. S., Delen D. [2022], The use of multi-criteria decision-making methods in business analytics: A comprehensive literature review, Technological Forecasting & Social Change, 174: 1–35.
Yaşar M., Asker V., Özdemir E. [2018], Effıcıency measurement at airline city-pair markets wıth data envelopment analysıs, in: 4th Global Business Research Congress: 1–5, PressAcademia Procedia, Istanbul.
Yu M.‑M., Chang Y.‑C., Chen L.‑H. [2016], Measurement of airlines’ capacity utilization and cost gap: Evidence from low-cost carriers, Journal of Air Transport Management, 53 (2): 186–198.
Yu M.‑M., Chen L.‑H., Chiang H. [2017], The effects of alliances and size on airlines dynamic operational performance, Transportation Research Part A, 7 (106): 197–214.
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